Spectrographic analyzers are used in a variety of medical and industrial applications to analyze the composition of a gaseous or fluid sample. One such application is the use of a spectrographic gas analyzer to monitor respiratory, anesthetic and/or other therapeutic gases in a patient respiratory flow line during a medical procedure. The operation of such analyzers typically involves illuminating a sample gas, measuring the illumination intensity, or other value related to the illumination transmitted through the sample gas, at various wavelengths, and analyzing the measured values based on known transmission/absorption/scattering characteristics of the components of interest to determine the composition of the sample gas, e.g., the concentration of components of interest in the sample gas. The number of wavelength measurements employed can vary depending on system requirements, but is generally at least as great as the number of components to be analyzed. The set of wavelength-related measurements for a given sample gas may be considered a composite measured spectrum.
The process for deriving individual component information from the composite measured spectrum involves isolating effects due to the component or components under analysis. In this regard, it will be appreciated that various interfering components of the sample gas may have overlapping effects such that the measured value at a given wavelength may reflect effects due to more than one component. The process for deriving individual component information from the composite measured spectrum is well known in the prior art, and involves the derivation of "calibration vectors" which can be used to calculate the concentration of individual components of the sample mixture. In general, there is one calibration vector for each component to be measured, and the measurement produced using each calibration vector will respond only to the presence of a single component of the sample mixture. The process for deriving individual component information therefore involves at least a composite measured spectrum and one or more vectors.
In order to obtain reliable information, it is important for the spectrometer to be carefully calibrated. Such calibration involves, inter alia, establishing and maintaining a known relationship between particular measured values and corresponding wavelengths such that the composite measured spectrum can be properly processed using the predetermined vectors. It is known that various factors can affect this relationship depending on the particulars of the equipment. For example, a change in temperature may result in a slight change in instrument geometry or dimensions which, in turn, may cause a wavelength shift in the composite measured spectrum unrelated to the composition of the sample gas. Such a shift, if not accounted for, introduces an element of error into the system and could result in significant hazards, particularly in medical applications.
Two general approaches to addressing this source of potential error are measurement drift prevention and measurement drift correction. Measurement drift prevention attempts to avoid drift by maintaining temperature or other parameters at a constant value. However, this approach requires careful monitoring and control which increases instrument complexity and can be impractical. Measurement drift correction attempts to identify a drift of the composite measurement spectrum due to temperature or other parameters, and then correct the composite measurement spectrum based on the identified drift. This approach, however, generally involves substantial processing and dedicated processor resources, particularly in applications involving high measurement rates and multiple interfering components where the composite measurement spectrum may have a complex form. These approaches have thus resulted in substantial instrument complexity, processing complexity and/or processor requirements.